Segmentation of coronary artery tree from computed tomography angiography using region growing method

Abstract

Recently, automated analysis of medical images becomes important for easier and faster clinical diagnosis. Identifying human organs is the key component for such analysis, i.e., segmentation of the anatomical structures from medical images. Coronary arteries segmentation gained wide interest in old and recent scientific research, thus various methods have been developed for segmenting coronaries from different cardiac imaging modalities. This paper provides a review of studies based on region growing (RG) method in segmentation of coronary arteries from computed tomography angiography (CTA). The main objective of this paper is to highlight the different perspectives of applying RG in the segmentation process. Firstly, medical background is provided to coronary disease, CTA and RG algorithm explanation. Finally, the studies are compared to each other according to the selection of seed points, detection of seed points, preprocessing and enhancements, RG segmentation process and finally the post-processing.